:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wallace, Ewan R. S., Frey, Nathan C., Rackers, Joshua A.
Format:	Preprint
Published:	2025
Subjects:	Chemical Physics Machine Learning
Online Access:	https://arxiv.org/abs/2503.13352
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Vibrational Fingerprints of Strained Polymers: A Spectroscopic Pathway to Mechanical State Prediction
by: Konrad, Julian, et al.
Published: (2025)

QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials
by: Zariquiey, Francesc Sabanés, et al.
Published: (2025)

Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems
by: Scherbela, Michael, et al.
Published: (2025)

Machine Learning Integrated Near-Infrared Surface-Enhanced Raman Spectroscopy for Accurate Strain-Level Virus Identification
by: Zhang, Na, et al.
Published: (2025)

Accurate Computation of Quantum Excited States with Neural Networks
by: Pfau, David, et al.
Published: (2023)

Generalizable, Fast, and Accurate DeepQSPR with fastprop
by: Burns, Jackson, et al.
Published: (2024)

Preserving Surface Strain in Nanocatalysts via Morphology Control
by: Shi, Chuqiao, et al.
Published: (2024)

Stable and Accurate Orbital-Free DFT Powered by Machine Learning
by: Remme, Roman, et al.
Published: (2025)

Highly Accurate Real-space Electron Densities with Neural Networks
by: Cheng, Lixue, et al.
Published: (2024)

High Pressure Suppression of Plasticity due to Over-Nucleation of Shear Strain
by: Hamilton, Brenden W., et al.
Published: (2024)

The Bigger the Better? Accurate Molecular Potential Energy Surfaces from Minimalist Neural Networks
by: Käser, Silvan, et al.
Published: (2024)

Reaction-Level Consistency within the Variational Quantum Eigensolver: Homodesmotic Ring Strain Energies of Cyclic Hydrocarbons
by: Roy, L., et al.
Published: (2026)

NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models
by: Qiao, Zhuoran, et al.
Published: (2024)

Tailoring Photoluminescence by Strain-Engineering in Layered Perovskite Flakes
by: Spirito, Davide, et al.
Published: (2024)

Accurate and efficient structure elucidation from routine one-dimensional NMR spectra using multitask machine learning
by: Hu, Frank, et al.
Published: (2024)

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning
by: Lin, Haitao, et al.
Published: (2025)

Accurate machine learning force fields via experimental and simulation data fusion
by: Röcken, Sebastien, et al.
Published: (2023)

A Descriptor Is All You Need: Accurate Machine Learning of Nonadiabatic Coupling Vectors
by: Martinka, Jakub, et al.
Published: (2025)

A Scalable and Quantum-Accurate Foundation Model for Biomolecular Force Field via Linearly Tensorized Quadrangle Attention
by: Su, Qun, et al.
Published: (2025)

On the design space between molecular mechanics and machine learning force fields
by: Wang, Yuanqing, et al.
Published: (2024)

Automatic Algorithm Switching for Accurate Quantum Chemical Calculations
by: Imamura, Satoshi, et al.
Published: (2024)

A Novel 4-D Dataset Paradigm for Studying Complete Ligand-Protein Dissociation Dynamics
by: Li, Maodong, et al.
Published: (2025)

MoleculeCLA: Rethinking Molecular Benchmark via Computational Ligand-Target Binding Analysis
by: Feng, Shikun, et al.
Published: (2024)

Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule?
by: Schwarting, Marcus, et al.
Published: (2024)

A Systematic Evaluation of Molecular Mixture Behavior Prediction
by: Leenhouts, Roel J., et al.
Published: (2026)

OrbitAll: A Unified Quantum Mechanical Representation Deep Learning Framework for All Molecular Systems
by: Kang, Beom Seok, et al.
Published: (2025)

Swallowing the Bitter Pill: Simplified Scalable Conformer Generation
by: Wang, Yuyang, et al.
Published: (2023)

OpenQDC: Open Quantum Data Commons
by: Gabellini, Cristian, et al.
Published: (2024)

Projected Hessian Learning: Fast Curvature Supervision for Accurate Machine-Learning Interatomic Potentials
by: Rodriguez, Austin, et al.
Published: (2026)

Parametrized Quantum Circuit Learning for Quantum Chemical Applications
by: Jones, Grier M., et al.
Published: (2025)

Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models
by: Xie, Yu, et al.
Published: (2026)

Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties
by: Vinod, Vivin, et al.
Published: (2024)

Interpretable Machine Learning for Quantum-Informed Property Predictions in Artificial Sensing Materials
by: Chen, Li, et al.
Published: (2026)

QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
by: Vinod, Vivin, et al.
Published: (2024)

Complete and Efficient Covariants for 3D Point Configurations with Application to Learning Molecular Quantum Properties
by: Maennel, Hartmut, et al.
Published: (2024)

XANE(3): An E(3)-Equivariant Graph Neural Network for Accurate Prediction of XANES Spectra from Atomic Structures
by: Grizzi, Vitor F., et al.
Published: (2026)

Active Learning Enables Extrapolation in Molecular Generative Models
by: Antoniuk, Evan R., et al.
Published: (2025)

Molecule Generation and Optimization for Efficient Fragrance Creation
by: Rodrigues, Bruno C. L., et al.
Published: (2024)

Autotuning T-PaiNN: Enabling Data-Efficient GNN Interatomic Potential Development via Classical-to-Quantum Transfer Learning
by: Pelletier, Vivienne, et al.
Published: (2026)

$\nabla^2$DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network Potentials
by: Khrabrov, Kuzma, et al.
Published: (2024)